Western European imports

Transpn. Res:A. Vol. 23A. No. 5, pp. 367-375. Printed in Great Britain.

0191-2615’89 $3.C@+ .W 0 1989 Pergamon Press plc

1989

CONSUMER VALUATION OF NEW CAR ATTRIBUTES: AN ECONOMETRIC ANALYSIS OF THE DEMAND FOR DOMESTIC AND JAPANESE/ WESTERN EUROPEAN IMPORTS P ATRICK S. MC C ARTHY and R ICHARD T A Y Department of Economics, Purdue University, West Lafayette, IN 47907, U.S.A. (Received 30 April 1988; in revised form 22 December 1988)

Abstract-Although previous studies of new vehicle choice decisions have shown that consumers evaluate the attributes of domestic vehicles differently from those of imported vehicles, the assumption underlying these results is overly restrictive. In particular, there is no reason to assume, a priori, that the attributes of all imported vehicles have similar effects upon consumer choice behavior. A competing hypothesis, for example, is that consumers of U.S. and European automobiles have similar attribute valuations that are differentiated from those of Japanese consumers. In the present paper, a multinomial logit model of vehicle type choice is developed which more completely differentiates imports by country of origin. Using a 1985 national sample of new car buyers to estimate the model, willingness to pay measures were calculated and nested hypothesis tests on attribute valuation performed. The results supported the hypothesis that consumers value vehicle attributes differently depending upon its country of origin. Moreover, consumers do not have similar valuations on the attributes of all imports implying that an arbitrary distinction between domestic and imported vehicles may produce misleading results.

decision. Typically, a dummy variable, which reflects a foreign/domestic dichotomy, is introduced into the model to control for those characteristics which differ by country of origin but are not explicitly in the model (primarily due to absence of data}. Similar to Lave and Bradley, for example, Manski and Sherman (1980), found tht households living on the coast were less likely to own a domestic vehicle. In a more recent study, Mannering and Winston (1987) concluded that, all else held constant, American consumers exhibit a weak preference for foreign relative to domestic vehicles. An underlying assumption in virtually all disaggregate vehicle type choice models is that the effect of each attribute on vehicle choice is independent of country of origin. In other words, the importance of fuel efficiency (or any other vehicle attribute) to a consumer’s choice of a domestic vehicle is identical to that of a foreign vehicle. In reality, this may not be true. Suppose, for example, that foreign manufactured automobiles are more fuel efficient and domestic vehicles more comfortable. Then, given the same budgetary constraint set, two individuals with different preferences may not select the same vehicle. An individual with a preference for greater fuel efficiency would be willing to sacrifice a larger amount of other vehicle attributes to obtain a unit increase in fuel economy. Consequently, he would be more likely to purchase the foreign vehicle. Conversely, an individual with a preference for comfort and interior space, and thus willing to forego few other attributes for a unit increase in fuel economy, would be expected to purchase the domestic vehicIe. In general, then, if there is a systematic relationship between vehicle attributes and country of origin,

INTRODUCTION During the past twenty five years, the U.S. automobile industry has experienced significant, and successful challenges from its world wide competitors. Between 1960 and 1984, import market share in-

creased from 7.6% to 24.9%. Moreover, the increase in import market share has been disproportionately in favor of Japan. Between 1960 and 1984, for example, Japan’s share of the U.S. automobile market increased from 0% to 18.3% (Altshuler ef al., 1984). At least partially in response to the increasing market share of imported vehicles, research interests began to focus upon consumer vehicle choice activities. More specifically, a variety of disaggregate models were developed and estimated which analyzed the underlying determinants of the number and type of vehicle choices as well as the intensity of vehicle use (Hensher, 1985). Although extant research on vehicle choice decision-making is extensive, relatively little research has explicitly centered upon the domestic/import decision. In one of the few studies on this issue, Lave and Bradley (1980) estimated a model of imported automobile market penetration which identified various determinants of imported car ownership. As the development of more sophisticated discrete choice modelling methods evolved, the import/domestic distinction played a minor role in determining vehicle type choices. Since, in disaggregate vehicle type choice models, vehicles are characterized by a set of attributes, country of origin is only important to the extent that the model is not fully generic, that is, does not include all vehicle attributes relevant to an individual’s 367

368

P. S. MCCARTHY and R. T.&Y varying preferences among the population will pro- sible by interacting vehicle attributes with each of duce differing attribute valuations. three dummy variables that correspond to the counIn a recent paper, Mannering and Mahmassani try of origin. This leads to the following general (1985) investigated this issue and found evidence for specification of mean utility differing attribute valuations on vehicle operating costs, horsepower, expected collision costs, and a Consumer’s Report cost index. Based upon their analysis, the authors concluded that domestic man- where the subscripts a, j, and e correspond, respecufacturers would benefit through improvements in tively, to the United States, Japan, and Europe. TOi, performance, safety, and reliability. for example, equals (z, .A)whereA = lifthe The purpose of this study is to extend Mannering vehicle was produced in the United States and 0 and Mahmassani’s analysis. Although Mannering otherwise. Various nested hypotheses can be derived and Mahmassani found evidence for differing attrib- from the specification in eqn 2. For example, Manute valuation, their analysis assumes that individuals nering and Mahmassani’s model assumed that pj = place identical valuations upon the attributes of all PC. Consequently, the mean utility for vehicle type foreign vehicles. Although this is a plausible hy- i in their framework is expressed as pothesis for vehicles produced in the Pacific rim areas, it is less plausible for European produced veVi” = PZ?” + P; 2,s (3) hicles. Relative to Japan, automobiles produced in Europe tend to be larger, more powerful, and more where the subscript f refers to “foreign”. Defining expensive-attributes which are more closely Fto be 1 for non-American vehicles and 0 otherwise, aligned with American produced vehicles. An alter- then a,, equals (z, 1 F). native hypothesis, then, is that U.S. consumers place Using the general model given by eqn 2, alteridentical valuations on the attributes of European native nested hypotheses on attribute valuation will and U.S. automobiles relative to those produced in be examined. Japan. This study will test alternative attribute valuation hypotheses which can be identified from a general model of vehicle type choice. DATA In section 2 of the paper, a model of vehicle type Data for this analysis came from a 1985 national .choice is developed from which nested hypotheses survey of new car buyers, conducted by J. D. Powers on attribute valuation are identified, section 3 discusses the data, section 4 presents estimation and and Associates, and the Automobile Club of Southhypothesis test results, and section 5 summarizes the ern California, which provided vehicle attribute information on new make/models.? The survey analysis and offers concluding comments. obtained information on multiple facets of new vehicle purchase decisions, including a description of the new vehicle purchased, purchasing and financing METHODOLOGY arrangements, source of sales by make and market segment of vehicle, owner loyalty, and socio-ecoMultinominal logit analysis will be used to estimate a general model of vehicle type choice for a nomic characteristics of the principal purchaser and household. In addition, since 1984, the Automobile population of utility maximizing consumers. As is Club has evaluated currently manufactured four paswell documented in the literature (Ben-Akiva and senger vehicles on various design characteristics, inLerman, 1985; Train, 1986), the probability that including cost, acceleration, interior space, interior dividual n purchases vehicle type i is noise, fuel economy, handling, size, ride quality, ease of entry and exit, luggage capacity, and turning (1) circle. From these two sources, a usable data set containing 4,902 households and 68 make/models was developed. Moreover, in order to insure that the where p is a vector of parameters to be estimated sample of observations was representative of the new and zk,, (k = 1, . . . , K) is a vector of observable car population, observations in this data set were vehicle and socio-economic characteristics for indiweighted in the same proportion as annual registravidual n. j3’zk,, (k = 1, . . . , K) can be interpreted tion figures. Since the original sample was stratified as a linear-in-parameters mean utility of vehicle type on the make/model of vehicle, the sample was choice k for individual n. based. In general, estimating the parameters of a In this analysis, vehicle productionoccurs in one choice based sample using exogenous sample maxof three areas: the United States, Japan, or Europe. If there is a systematic relationship between production source and attribute valuation, then the multinominal choice model can accommodate fFor an expanded discussion on the development of the usable data set, see McCarthy (1987). preference differences in the population. This is pos-

Consumer valuation of new car attributes 369 Education offers perhaps the most striking delineimum likelihood yields inconsistent estimates. HOWever, in the special case where the sampling fraction ation between those who buy American cars and is chosen to equal the population shares, exogenous those who buy foreign manufactured automobiles. sample maximum likelihood is appropriate (Ben- As education level increases, the relative share of Akiva and Lerman, 1985, p. 237). Table 1 profiles domestic to foreign car buyers falls, an observation new car purchase decisions from the weighted data which is consistent with a hypothesis by Lave and Bradley (1980) that more educated individuals tend set. There are several interesting observations which to be proenvironmentalist and antiestablishment, can be made from Table 1. First, with the exception both of which imply, all else held constant, an inof households with 4 or more vehicles, a similar pro- crease in the probability of purchasing an imported vehicle. This latter point was separately found in a portion of households with 1, 2, or 3 vehicles purchase domestic, European, and Japanese cars. With study by McCarthy and Farmer (1987). With respect to family size, Table 1 reports that respect to households with 4 or more vehicles, a slightly larger proportion of households purchase the relative share of domestic car buyers increases non-American vehicles. The origin of new vehicle with family size. This reflects the fact that U.S. manpurchased does vary, however, by age. In particular, ufactured vehicles, on average, are larger and better young car buyers purchase relatively more Japanese accommodate the needs of larger households. This cars than do buyers who are twenty-five and older. is not true, however, for two members households Similarly, individuals over the age of forty-five buy where there is a relative preference for European relatively fewer Japanese cars than their younger vehicles. Last, with respect to brand loyalty, concounterparts. Comparing between income groups, sumers exhibit stronger ties to U.S. manufactured note that households with less than $40,000 buy rel- vehicles than do buyers of non-U.S. manufactured atively more Japanese cars while those who earn automobiles. between $40,000 and $60,000 purchase relatively Although the weighted data set summarized in more American cars and people earning more than Table 1 contained all of the relevant socioeconomic $60,000 have a relative preference for European and vehicle data, computer constraints precluded uscars. Given that the median 1985 purchase price of ing the entire data set to estimate the model. ThereAmerican European, and Japanese vehicles was fore, a sample was drawn from the 4,902 usable data $11,161, $17,000, and $10,755, respectively, it is set. Moreover, to guarantee that the estimated palikely that these findings reflect an income effect. rameters of the model will be consistent, the sample

Table 1. New car purchase profile of usable data set Domestic European Japanese Number of Vehicles in Household

24 Age of Owner Under 24 25-44 Over 45 Household Income Under $20,000 $20,000-$39,999 %40,000-$60,000 Over $60,000 Owner Education < High School Graduate Trade?Fechnical School Hieh School Graduate Atiknded College Household Size 1

Brand Loyalty New Make Same make as Previous Car

60.50 65.42 60.72 55.42

6.76 7.92 7.51 10.41

32.74 26.66 31.77 34.17

47.36 58.36 73.49

4.68 8.81 6.86

47.96 32.83 19.65

57.82 63.51 69.76 50.00

5.33 4.89 7.26 15.60

36.85 31.60 22.98 34.40

87.07 75.32 73.73 56.68

2.47 4.54 6.06 8.87

10.46 20.14 20.21 34.45

48.50 62.17 62.15 68.02

11.73 9.58 5.68 6.00

39.76 28.25 32.17 25.98

59.52

8.34

32.14

72.69

5.85

21.46

P. S. MCCARTHY and R. TAY

370

was drawn under the constraint that the sample proportion of each of the 68 make/models represented in the usable data set equalled the proportion in which each of these are represented in the population (IvlcFadden, 1978). This sampling strategy resulted in a random sample of 726 observations. Comparing the mean values on a large number of vehicle and socio-economic characteristics revealed that the random sample was representative of the larger sample. Finally, for estimating the model, it was necessary to define an alternative choice set. Fourteen randomly selected vehicles were drawn from the set of feasible make/models and assigned to each of the

726 observations in the estimation sample. These 14 assigned alternatives combined with an individual’s chosen alternative gives each observation a choice set of 15 make/models.

ESTIMATION RESULTS Table 2 presents the variables used in estimating the model. In general, it is expected that increases in each of the cost related attributes as well as in acceleration times and the number of seconds to complete a slalom course will reduce the probability of purchasing a vehicle, all else held constant. On

Table 2. Cost Related Attributes

Purchase Price/Household Purchase price of vehicle divided by annual household income.’ Income Operating Cost Performance Related Attributes

Acceleration Slalom Reliability Space Related Attributes

Interior Space Trunk Size Comfort Related Attributes

Door Sill Height Dashboard Accessibility Interior Noise Level

Safety Related Attributes

Safety Vehicle Size Other Attributes Brand Loyalty American Motors Chrysler Ford European

Per mile fuel cost, defined as the average gasoline price in respondent’s home state divided by the EPA’s fuel economy for city i driving.

-Number of seconds required to reach a speed of 60 MPH from a standstill.* Number of seconds required to complete a slalom test course.’ An index representing the incidence and quality of dealer maintenance and repair work on a newly purchased vehicle.’ The sum of front/rear leg room and shoulder room.:’ Number of cubic feet of cargo volume soecified in the EPA Fuel Economy guide. _ Door sill height, in inches The horizontal distance from the windshield to the seat back measured 25 inches vertically from the front lower seat cushion. Interior noise level (in decibels) at a speed of 30 MPH. Dummy variable which equals 1 if vehicle is identified as one of the most crashworthy vehicles in the 1985 model year, 0 otherwise.h Vehicle length times vehicle width, in inches. Dummy variable which equals 1 if new vehicle purchased is of the same make as the respondent’s previous vehicle, 0 otherwise. Dummy variable which equals 1 if vehicle is manufactured by American Motors Corporation, 0 otherwise. Dummy variable which equals 1 if vehicle is manufactured by Chrysler Corporation, 0 otherwise. Dummy variable which equals 1 if vehicle is manufactured by Ford Motor Company, 0 otherwise. Dummy variable which equals 1 if vehicle is manufactured in Europe, 0 otherwise. Dummy variable which equals 1 if vehicle is manufactured in Japan, 0 otherwise.

‘The purchase price is defined as the manufacturer’s base vehicle price, adjusted for engine option, transmission option, freight, and California emission system. *Four acceleration tests were performed. The average of these is used in this analysis. ‘Based upon a test developed by Motor Trend Magazine, the test course is 800 feet long and 100 feet wide. Each vehicle is tested three times on the course. Slalom is an average of the three test scores. ‘The index is calculated by J. D. Powers and Associates. A higher number indicates better performance on this dimension. ‘Front leg room is measured from the accelerator pedal heel point up over the lower seat cushion to the seat back. Rear leg room is measured from the rear of the front seat back, horizontally to rear seat lower cushion, down the lower cushion to the intersection of the rear seat back and rear lower cushion. Front (rear) shoulder room is measured laterally across the width of the vehicle at a height of 18 inches vertical from the intersection of the front (rear) seat back with the lower seat cushion. %ee The Car Book by Jack Gillis, 198.5 Edition. For each size class of vehicle, a crash test index is calculated based upon occupant protection in a frontal crash at 35 MPH.

371

Consumer valuation of new car attributes the other hand, with the exception of Noise, each

of the comfort related variables is expected to increase the purchase probability, all else held constant. Since increasing interior noise levels reduces a vehicle’s attractiveness, it is expected to decrease the probability of purchase. Also, note that Door Sill Height is included to reflect the ease of entering and exiting the vehicle and Dashboard Accessibility is intended to reflect the overall convenience of dashboard controls to the driver. Although an increase in Dashboard Accessibility is expected to decrease purchase probabiiity, this is actually a net effect. The Automobile club of Southern California calculated this distance because it has implications for occupant protection. In general, the further one is from the dashboard, the less severe will be any injuries suffered in the event of an accident. Notwithstanding its safety implications, all subsequent analyses found a negative net effect. Since Safety and Vehicle Size are expected to improve occupant safety,4 each of these variables is expected to increase, all else held constant, purchase probability. On the other hand, the net effect of trunk space on purchase probability is ambiguous. Although an increase in trunk space raises cargo capacity, this positive effect on purchase probability may be offset by a change in some other attribute, such as styling (e.g., hatchback versus notchback), since vehicle size and interior space are also included in the model. Brand loyalty is expected to increase the probability of purchase and last, geographic and manufacturer alternative specific variables are included to reflect any omitted variables that affect the type choice decisions of households. General Motors is the normalizing manufacturer. Table 3 reports the estimation results for the most general case when each explanatory variable is disaggregated according to whether the a vehicle’s country of origin was the United States, Japan, or Europe. In general, the overall fit of the model is good, and, with some exceptions, each of the variables carries its hypothesized sign. These “anomalies,” however, have been identified in other studies and appear to be quite robust to specification. For example, operating cost is an important attribute for domestic vehicles and European produced vehicles but statisticahy insignificant for vehicles produced in Japan. To test the sensitivity of this, various specifications were tried and produced similar qualitative results. In a hedonic regression analysis of automobile quality, Feenstra (1984) found gas mileage to be statistically insignificant for Japanese cars but significant for domestic cars. Since the operating cost variable used in this study is based upon EPA’s fuel economy data, the results presented in Table 3 are consistent with Feenstra’s findings. Thus, given that the Japanese fleet of vehicles are relatively more fuel $Since Vehicle Size is highly correlated with vehicle weight, it is expected to reflect occupant safety. Vehicle Size was included in the model rather than vehicle weight because it led to an improved fit.

efficient, it is not surprising that operating cost is not an important attribute in one’s choice decision. With respect to vehicle performance, Acceleration carries a positive sign for American and Japanese vehicles. This is a result that has been obtained elsewhere, which suggests that manufacturers may be overrating consumer preferences for acceleration. Manski and Sherman (1980) offer two data related Table 3. Estimation results-model of new vehicle purchases Independent Variable Purchase Price/Household Income (A) Purchase Price/Household Income (E) Purchase Price/Household Income (J) Operating Fuel Cost (A) Operating Fuel Cost (E) Operating Fuel Cost (J) Acceleration (A) Acceleration (E) Acceleration (J) Slalom (A) Slalom (E) Slalom (J) Reliability (A) Reliability (E) Reliability (J) Interior Space (A) Interior Space (E) Interior Space (J) Trunk Size (A) Trunk Size (E) Trunk Size (J) Interior No& Level (A) Interior Noise Level (E) Interior Noise Level (J) Door Sill Height (A) Door Sill Height (E) Door Sill Height (J1 Dashboard A&es&ility (A) Dashboard Accessibility (E) Dashboard Accessibility (J) Safety (A)* Safety (J) Vehicle Size (A) Vehicle Size (El Vehicle Size (J) Brand Loyalty** American Motors Chrysler Ford European Japan

Coefficient Estimate

Asymptotic f-statistic

-3.870

-5.73

-7.081

-6.73

-4.173 - 537 - .426 - .0030 .089 -.159 .116 - .459 - 1.236 -2.217 .0059 .0275 .0065 .049 .045 .191 - .0245 - .1843 .0028 - .1530 .0012 .0112 .189 .272 - .2ss - .025 - .065 - .096 1.182 .507 .0003 .0008 .0003 1.99 .0719 .6246 .OOlS - 4.0453 - 14.5077

-4.85 -2.68 -1.60 - .Ol 1.55 - 1.13 1.98 - 1.51 -1.04 -4.66 1.12 3.00 1.17 2.93 1.31 5.88 -2.99 -3.32 .I7 - 4.71 .02 .22 4.38 2.08 -2.95 -1.13 -1.05 -1.73 6.14 2.00 2.46 3.29 1.44 16.34 .15 2.93 .Ol - .29 - 1.72

Number of households: 726 Number of observations: 10,890 Log-likelihood at 0: 1966.0 Log-likelihood at convergence: 1554.1 x2 = 823.90 $.05(38) = 53.38 *Based upon the government crash tests, none of the European cars included in this analysis was found to be very crashworthy. **The relatively small number of individuals that demonstrated a brand loyalty led to convergence problems when the variable was disaggregated by manufacturing region.

372

P. S. M CCARTHY

explanations. First, there is the possibility of correlation between acceleration and omitted and/ or included variables. Second, the choice set alternatives do not distinguish between engine sizes for a given vehicle model. Although the first reason may explain the observed signs, the second reason is not relevant. For this study, an eight digit vehicle identification number was defined to reflect make/ model, body style, engine type, number of cylinders and transmission type. This id number was then used to match vehicles purchased with vehicles tested by the Automobile Club of Southern California. Slalom, on the other hand, carries its hypothesized sign and is statistically significant for Japanese and European (at the .l level) produced vehicles. And, vehicle reliability increases purchase probabilities although the effect is significant for European cars only. Interior Space significantly increases the probability of purchase, all else held constant, regardless of where the vehicle is produced. Trunk space, on the other hand, significantly reduces purchase probability for U.S. and European vehicles while having no effect upon purchase behavior for Japanese vehicles. As discussed above, this suggests that increasing trunk space, holding all else constant, may negatively affect some excluded attribute resulting in a net decrease in purchase probability. Vehicle comfort is seen to have its expected effect upon vehicle demands although interior noise levels only affect the probability of purchasing an American vehicle. Note also that, for American and European vehicles, door sill height, which reflects ease of entry and exit, is positive and significant. For Japanese vehicles, there is a negative effect, indicating that door sill height may be picking up excluded attributes. For example, higher door sill heights may affect the handling/stability and/or styling/aeordynamics of the car. A similar result was reported by Feenstra (1988) in which the height of Japanese cars produced a negative effect on perceived quality. Vehicle size is positively valued, although it is not significantly different from 0 (at the .05 level) for vehicles produced in Japan and vehicle safety, all else held constant, significantly increases the probability of purchase. Moreover, the effect is greater for American relative to Japanese produced vehicles, an interesting result given that, on average, US. vehicles are larger and heavier. Finally, with respect to domestic manufacturers, it is seen that from Table 3 that, relative to General Motors, there is a preference for Chrysler and against Japanese produced automobiles. In sum, the model reported in Table 3 provides a good representation of vehicle choices when all attributes are delineated by country of origin. An important implication of these results is that, relative to less general specifications of vehicle choice models, vehicle attributes can have different effects on purchase behavior depending. For example, less

and R. TAY

general models of vehicle choice typically find that improvements in fuel economy raise the probability of purchase. The results reported in Table 3, however, indicate that this result depends upon a vehicle’s country of origin. More accurately, it depends upon the characteristics of the vehicle fleet manufactured by the country. Since, on average, the Japanese automobile fleet have higher levels of fuel economy than the American and European counterparts, one would expect fuel economy improvements by the Japanese to have smaller effects on vehicle purchase decisions than those accomplished by American and European producers. Such an effect was observed in the present analysis. A second implication of the model relates to the inclusion, relative to most studies, of a larger number of vehicle characteristics. Difficulties exist in recognizing and incorporating the relevant trade-offs between attributes. For example, an individual may trade-off styling considerations for ease of entry/ exit from the vehicle. Defining and empirically representing this concept in a choice model is not a simple task. Moreover, it is not feasible to consider all possible choice combinations of trade-offs. Therefore, the presence of anomalies does not necessarily imply a poor empirical specification of the model. In this analysis, for example, the results were robust with respect to alternative specification, given the available data. Indeed, a richer model specification which identifies anomalies may provide an analyst with information on attribute trade-offs that are camouflaged by more aggregate specifications. Tables 4 and 5 present willingness to pay implications from the estimated model for each of the statistically significant attributes in Table 3. The generic columns report similar figures under the hypothesis that p. = Pe = pi, where a, e, and j reflect American, European, and Japanese, respectively. Each of the attributes for the restrictive model was significantly different from 0 at a .05 level of significance. Consumers of U.S. automobiles place a higher premium (in absolute terms and relative to the median car price) upon fuel efficiency. In addition, they value more highly a vehicle’s handling capabilities, ease of entry/exit, reductions in interior noise, and vehicle size. Consumers of European vehicles, on the other hand, place higher values upon ease of entry/exit, interior space, and reliability whereas they place greater negative values upon trunk space. Last, buyers of Japanese vehicles attach a higher price, in terms of capital cost, to improvements in handling and interior space, dashboard accessibility, and vehicle size; Conversely, acceleration improvements and increases in door sill height are valued much lower. NESTED HYPOTHESIS TESTS

Relative to the general model estimated in the previous section, a series of submodels will be estimated to test various nested hypotheses on the

Consumer valuation of new car attributes

373

Table 4. Willingness to pay measures (in capital cost)* Change in Attribute 1 cent decrease in fuel cost 1 second decrease in acceleration time 1 standard deviation decrease in slalom time 1 cubic inch increase in interior space 1 cubic foot increase in trunk space 1 inch increase in door sill height 1 inch closer to dashboard 1 decibel decrease in interior noise 100 sq inch increase in exterior size

1 point increase in reliability index

Domestic

Eurooean

Jaoanese

Generic

5005 -830 2226 457 - 224 1763 1427 265 -

2172 229 - 938 1387 145 140

- 1004 4414 1653 - 2593 831 284 -

2235 - 630 1809 537 - 224 1204 289 1064 157 67

*The willingness to pay measures are based upon a median income value of $36,100 and are calculated for all variables that were significant at the .1 level or higher. The median car price from the J. D. Power national survey was $i1,168.

coefficients. The appropriate statistic for testing these hypotheses is defined as -2(L*(P,) - L’(P”)) where L*@,) and L*(p,) is the log-likelihood function at convergence for the restricted and unrestricted models, respectively. For N and K estimated parameters in the unrestricted and restricted models, respectively, this statistic is chi-square distributed with (N-K) degrees of freedom. Table 6 presents hypothesis test results assuming that PC = pi, /3. = p., and PO = @,, respectively. For the foreign/domestic dichotomy, Table 6 indicates that, with respect to the complete set of coefficients, the null hypothesis is soundly rejected. Moreover, for subsets of variables, which correspond to cost, space, comfort, and performance dimensions, the null hypothesis is rejected at the .Ol level in all cases. Recognizing that European imports may have attributes that are more similar to U.S. than Japanese automobiles, another set of statistical tests were run which equated attribute values for U.S. and European vehicles. Again, relative to the general model presented in Table 3, the null hypothesis is rejected, although the chi-square statistic is nearly half the value reported in Table 6. With respect to the group-

ings, the null hypothesis is rejected for three of the four groups. In particular, the null hypothesis that consumers of U.S. and European vehicles place similar values on vehicle comfort cannot be rejected at the .05 level. In part C of Table 6, a final nested hypothesis is tested wherein the consumers of U.S. and Japanese automobiles are hypothesized to place identical values on vehicle attributes. As seen in the table, the null hypothesis is rejected for the set of all variables. With respect to the subset of attributes, the null hypothesis cannot be rejected for the cost variables. To obtain further insight into this issue, the null hypotheses were tested for each attribute separately. In the first case, i.e. Fe = p,, the null hypothesis was rejected for capital cost, reliability, each of the space variables, and door sill height. A similar analysis under the hypothesis that Pe = /3. rejects the null hypothesis for capital cost, reliability, trunk space, interior noise, and vehicle size. Last, for the hypothesis that p. = pi, the null hypothesis is rejected for operating cost, slalom, interior space, noise, door sill height, and safety. In general, consumer attribute valuations based upon models with a simple domestic/foreign dichotomy are likely to produce misleading results. In addition, the results in Table 6 provide some evi-

Table 5. Willing&ess to pay measure (% median new car price)* Change in Attribute 1 cent decrease in fuel cost 1 second decrease in acceleration time 1 standard deviation decrease in slalom time 1 cubic inch increase in interior space 1 cubic foot increase in trunk space 1 inch increase in door sill height 1 inch closer to dashboard 1 decibel decrease in interior noise _ 100 sq inch increase in exterior size 1 point increase in reliability index

Domestic 44.8 -7.4 19.9 -;*; 15:s 12.8 2.4 -

European 12.7 1.3 -5.5 8.2 0.9 0.8

Japanese -9.3 41.0. 15.4 -23.2 7.7 2.6 -

Generic 20.0 -5.6 16.1 -24:: 10.8 2.6 9.5 ::“6

*The willingness to pay measures are based upon a median income value of $36,100 and are calculated for all variables that were significant at the .l level or higher. The median car price from the J. D. Power national survey was $11,168.

P. S. MCCARTHY and R. TAY

374

Table 6. Nested hypothesis tests Variables A l l Capital Cost, Operating Cost Interior Space, Trunk, Space Door Sill Height, Dashboard Accessibility, Interior Noise Acceleration. Slalom, Reliability, Vehicle Size

Restricted LL

-Z[LL(U)-LL(R)]

A. Null Hypothesis: p, = p? - 1582.2 56.2’

Number of Restrictions 11

- 1558.9

9.6*

2

- 1567.0

25.8*

2

- 1560.8

13.4*

3

- 1563.6

19.0:

4

B. Null Hypothesis: Se = l3. All Capital Cost, Operating Cost Interior Space, Trunk, Space Door Sill Height, Dashboard Accessibility, Interior Noise Acceleration, Slalom, Reliability, Vehicle Size

- 1569.2

30.2*

11

- 1559.8

11.4*

2

- 1561.0

13.8*

2

- 1557.2 - 1559.6

6.2”** 11.0*-

3 4

C. Null Hypothesis: S. = S, All Capital Cost, Operating Cost Interior Space, Trunk Space Door Sill Height, Dashboard Accessibility, Interior Noise Acceleration, Slalom Reliability; Vehicle Size

- 1581.3

54.2*

12

- 1556.1

4.0

2

- 1564.5

20.8”

2

- 1565.5

22.8*

3

- 1562.1

16.0*

4

*significant at .Ol level. **significant at .05 level. ***significant at .lO level.

dence that consumers value vehicle attributes similarly from countries which produce similar vehicles. In particular, adopting the assumption that Pe = pD relative to Pe = pi would lead to a better fit of the model, which reflects the fact that European vehicles are perceived to be closer to American than Japanese vehicles. However, this is a relatively weak statement, given the hypothesis tests on each attribute. In general, a preferred approach is to estimate a general model which imposes no restrictions and then streamline the model by testing a variety of hypotheses on the equality of coefficients. SUMMARY AND CONCLUS;ON

Previous analyses of vehicle type choices suggest that households place different valuations upon vehicle attributes depending upon whether the vehicle

is imported or domestic. Building upon this conclusion, the present analysis argues that it may be overly restrictive to consider all imported vehicles as homogeneous. In particular, it may be argued that vehicles imported from Europe are, on average, more similar to a representative domestic vehicle than a representative Japanese vehicle. From a 1985 nation wide survey of new car buyers, a general multinomial logit model of vehicle choice was estimated and used to test alternative nested hypotheses on vehicle attribute valuation. As found elsewhere, cost, performance, space, comfort, and safety characteristics are important determinants of vehicle choices. Calculated willingness to pay measures indicated that households place different valuations upon various attributes. Moreover, willingness to pay measures calculated from a model without differentiating by country of origin were

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Consumer valuation of new car attributes found to be widely different from those associated

with the more general model. This suggests that manufacturer price and/or investment decisions based upon attribute valuations from a restrictive model of vehicle choice could produce unexpectedly poor results. Supporting the conclusions obtained above, a series of nested hypothesis tests rejected the null hypothesis that attributes are similarly valued regardless of origin. Although, based upon tests for groups of attributes and for each attribute separately, the attributes of European automobiles have valuations more similar to American than Japanese cars, the evidence was not strong. In general, our results reject the hypothesis of similar attribute valuation for vehicles from any two areas of origin. It should be noted that consumer valuation may change with time and places since taste and preference will change in response to marketing and changes in the product line, social and economic conditions. For example, Mannering and Mahmassani utilizing data for 1978 new car purchase found a preference for foreign vehicles whereas our study shows a slight preference for domestic vehicles. Manski and Sherman’s study of both new and old car purchases in 1976 shows a preference for foreign vehicles but Train (1986) found a preference for domestic vehicles in his study of 1978 vehicle ownership. There exist, however, a set of factors affecting vehicle purchase and ownership which is consistent throughout the literature. One area for further research is the extent to which life cycle changes alter the differential valuations placed upon various vehicle attributes. For example, Mannering and Mahmassani (1985) and Manski and Sherman (1980) found significant differences in the valuation of weight by age of consumer. Age has also been important in the effect of acceleration (Manski and Sherman, 1980) and vehicle safety (McCarthy, 1987) upon choice. Related to this, additional work on the types of attribute trade-offs revealed in vehicle choice decisions is necessary. To illustrate, the present analysis found that vehicle weight increased and acceleration decreased the probability of purchase, all else held constant. Suppose weight is positively related to safety and performance but acceleration is negatively related to safety (i.e., “hotter” cars are less safe) and positively related to performance, then the results may imply that higher performance vehicles are preferred only if it does not result in a perceived reduction in safety. Whether this and other anomalous results found in the literature are valid implications awaits further work in the area.

An area for future research is whether a more complicated decision structure would lead to equal attribute valuations. In this analysis, households select from the entire set of make/models available to them. Suppose, however, that an individual’s choice of vehicle is conditioned upon vehicle size. In this instance, country OT origin would be more relevant to size of vehicle choice (some countries are better at producing smaller cars than larger cars, for example) but less relevant, given size, to actual vehicle chosen. Alternatively, a buyer might first make the foreign/domestic choice after which size of vehicle is decided. Moreover, given the results in this study that vehicle attribute valuations varied depending upon whether an individual purchased a domestic, European, or Japanese vehicle, a nested structure may provide insight into why a buyer is in a particular buyer group. REFERENCES Altshuier er al. (1984). The Future ofthe Automobik. Cambridge, MA: The MIT Press. Ben-Akiva M. and Lerman S. (1985). Discrete Choice Analysis. Cambridge, MA: The MIT Press. Feenstra R. (1984). Voluntary export restraint in U.S. autos, 1980-81: quality, employment, and welfare effects. In Robert E. BaIdwain and Anne 0. Krueger. (eds.)., The Structure and Evolution of Recent U.S. Trade Policy.

Chicago, IL: University of Chicago Press. Feenstra R. (1988). Quality change under trade restraints in Japanese autos. The Q. J. of Econ., 103, 131-146. Hensher D. A. (1985). Empirical vehicle choice and usage models in the household sector: a review. Ini/. J. Transport Econ., XII, 231-259. Lave C. and Bradley J. (1980). Market share of imported cars: a model of geographic and demographic determinants. Tramp. Res., 14A, 379-388. Mannering F. and Mahmassani H. (1985). Consumer valuation of foreign and domestic vehicle attributes: econometric analysis and implications for auto demand. Trans. Res., 19A, 243-25 1. Mannering F. and Winston C. (1987). U.S. automobile market demand. Chapter 3 in Clifford Winston and Associates. Blind Intersection. Washington D.C.: The Brookings Institution. Manski C. and Sherman L. (1980). An empirical analysis of household choice among motor vehicles. Trans. Rex, 14A, 349-366.

IMcCarthy P. S. (1987). The effect of automobile safety on vehicle type choice: an empirical analysis. Working Paper 924. Purdue University. McCarthy P. S. and Farmer A. (1987). An empirical study of import market share. Working paper. Purdue University. McFadden D. (1978). Modelling the choice of residential location. In A. Karlquist et al. (eds.). Spatial Interaction Theory and Planning Models. Amsterdam: North-HolIand Publishing Company. Train K. (1986). Quafitutive Choice Analysis. Cambridge, MA: MIT Press.